Improvement of PM2.5 predictions via variational assimilation of
Himawari-8 satellite AOD product

Abstract

Abstract: The aerosol optical depth (AOD) product of Himawari-8 satellite can be used to estimate PM2.5 concentration near the earth surface with wide spatial coverage and high temporal resolution. Based on the three-dimensional variational assimilation system, the PM2.5 data estimated by AOD are assimilated into the WRF-Chem atmospheric chemistry model. Then through the comparative analysis of control experiment and assimilation experiment, the improvement of PM2.5 pollution simulation by assimilation of PM2.5 data estimated by AOD is discussed. The results show that the assimilation of PM2.5 data estimated by AOD has a significant effect on the improvement of the background field, resulting in the significant improvement of PM2.5 pollution prediction. And in other hand, the improvement of PM2.5 pollution from AOD variational assimilation is different in time and space. In addition, compared with the other methods using AOD observation operators directly to assimilate AOD, this method has the advantage of easy operation.

Key words: WRF-Chem mode, Himawari-8 aerosol optical depth, PM2.5, geographically weighted regression

CLC Number:

TP79
P407

SUN Erchang , MA Jinji , WU Wenhan , YANG Guang , GUO Jinyu , . Improvement of PM2.5 predictions via variational assimilation of Himawari-8 satellite AOD product[J]. Journal of Atmospheric and Environmental Optics, 2023, 18(1): 59-72.

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Improvement of PM2.5 predictions via variational assimilation of Himawari-8 satellite AOD product

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